WO2023065477A1 - Procédé et appareil d'interrogation de texte spatial - Google Patents

Procédé et appareil d'interrogation de texte spatial Download PDF

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WO2023065477A1
WO2023065477A1 PCT/CN2021/135363 CN2021135363W WO2023065477A1 WO 2023065477 A1 WO2023065477 A1 WO 2023065477A1 CN 2021135363 W CN2021135363 W CN 2021135363W WO 2023065477 A1 WO2023065477 A1 WO 2023065477A1
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query
lower triangular
matrix
triangular matrix
vector
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PCT/CN2021/135363
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English (en)
Chinese (zh)
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苗银宾
杨玉涛
童秋云
范瑞彬
张开翔
李辉忠
李成博
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深圳前海微众银行股份有限公司
西安电子科技大学
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Publication of WO2023065477A1 publication Critical patent/WO2023065477A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/332—Query formulation
    • G06F16/3329—Natural language query formulation or dialogue systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/31—Indexing; Data structures therefor; Storage structures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
    • G06F16/374—Thesaurus
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/38—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/387—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location

Definitions

  • the invention relates to the field of financial technology (Fintech), in particular to a method and device for querying spatial text.
  • the selected query range is generally a preset range and shape; specifically, a preset coding algorithm is used to generate a gray code for the spatial geographic coordinates;
  • Figure 1 is based on The gray code schematic diagram of a kind of spatial geographic coordinates shown in the invention as an example, as shown in Figure 1, each cell (such as "0011") represents an area range, and spatial text data is recorded in the Gray code shown in Figure 1
  • Each object in the cluster for example, object P is located in the "0011" area).
  • the cell is used as the unit to determine the query range, for example, the query range is the area represented by "0011, 0010, 0111, 0110"; and then according to the text keyword of the query request, in The query result is determined in the query range of "0011, 0010, 0111, 0110".
  • Embodiments of the present invention provide a spatial text query method and device, which are used to query a query range of any shape, meet the query range actually required by the user, improve the accuracy of the query, and improve the accuracy of determining the query result.
  • the embodiment of the present invention provides a spatial text query method, including:
  • the query request includes a query range and a query keyword set;
  • the query range is a closed area formed by a query curve;
  • polynomial fitting is performed on the query curve, and the coefficients of each power term of the fitted polynomial are determined as a query range vector; based on the query range vector and the query keyword vector, get The first lower triangular matrix; encrypting the first lower triangular matrix through the first encryption matrix to obtain the query sub-trapdoor;
  • the object that meets the preset conditions is determined as the query result; wherein, the index of any object is the first obtained according to the spatial position and keyword set of the object.
  • the second lower triangular matrix is obtained after being encrypted by the second encryption matrix.
  • the query range is a closed area formed by the query curve, that is to say, the query range in the present invention can be of any shape; by determining the query keyword vector to realize multi-dimensional keyword query, the accuracy of keyword query is improved. degree; then determine the objects that meet the preset conditions through the fitting curve corresponding to the query curve, which is equivalent to determining the objects corresponding to the query keyword set and within the query range, so as to meet the query range actually required by the user, that is, query The result is within the query range actually required by the user, so the accuracy of the query is improved; and the query request and the information of the object are encrypted through an encryption matrix to ensure the security of the query.
  • the query keyword set is encoded to obtain a query keyword vector, including:
  • the keyword dictionary is obtained by taking the union of the keyword sets of each object in the space text data set;
  • the jth dimension element of the first vector is assigned a value of 0;
  • the first vector after the assignment of each dimension element is determined as the query key vector.
  • a first lower triangular matrix is obtained, including:
  • the second lower triangular matrix is obtained by the following methods, including:
  • the latitude value of the object is processed through n+1 latitude values of n+1 items and the longitude value of the object to determine the index space vector; the keyword set of the object is encoded to obtain index keyvector;
  • the query scope and the query keyword set of the query request are represented by the first lower triangular matrix; the spatial position and the keyword set of the object are represented by the second lower triangular matrix;
  • the second lower triangular matrix determines the objects corresponding to the query keyword set and within the query range, and determines the query result within the query range actually required by the user, thus improving the accuracy of the query.
  • assigning values to the diagonals of the first random lower triangular matrix according to the query range vector and each dimensional element in the query key vector includes:
  • the query scope and the query keyword set of the query request are expressed through a matrix, so that the amount of calculation is reduced when determining the query result, and the query efficiency is improved.
  • assigning values to the diagonals of the second random lower triangular matrix according to the index space vector and each dimensional element in the index key vector includes:
  • the first lower triangular matrix is encrypted by the first encryption matrix to obtain a query sub-trapdoor, including:
  • the index of any object is obtained after the second lower triangular matrix obtained according to the spatial position of the object and the keyword set is encrypted by the second encryption matrix, including:
  • the second lower triangular matrix obtained according to the spatial position of the object and the keyword set;
  • the index of the object is obtained by encrypting the second lower triangular square matrix according to the at least one random reversible square matrix, the third random lower triangular matrix and the fourth random lower triangular matrix.
  • the query request and the information of the object are encrypted through a random matrix to ensure the security of the query.
  • the query curve includes a first query curve and a second query curve; each of the query sub-trapdoors includes a first query sub-trapdoor and a second query sub-trapdoor; based on the query sub-trapdoor and the space
  • the index of each object in the text data set determines the object that meets the preset conditions as the query result, including:
  • the preset conditions include:
  • the absolute value of the trace of the first result matrix and the absolute value of the trace of the second result matrix are less than a first threshold; and the trace of the first result matrix is greater than a second threshold; the trace of the second result matrix less than the second threshold;
  • the first threshold is used to determine objects that meet the set of query keywords
  • the second threshold is used to determine objects conforming to the query scope.
  • the object corresponding to the query keyword set is guaranteed by the first threshold, that is, the keyword set contained in the object includes the query keyword set or is consistent with the query keyword set; Within the range, so as to realize the determination of the query result based on the threshold, improve the accuracy of the query and improve the accuracy of the determination of the query result.
  • an embodiment of the present invention provides a spatial text query device, including:
  • An acquisition module configured to acquire a query request;
  • the query request includes a query range and a query keyword set;
  • the query range is a closed area formed by a query curve;
  • a processing module configured to encode the set of query keywords to obtain a query keyword vector
  • polynomial fitting is performed on the query curve, and the coefficients of each power term of the fitted polynomial are determined as a query range vector; based on the query range vector and the query keyword vector, get The first lower triangular matrix; encrypting the first lower triangular matrix through the first encryption matrix to obtain the query sub-trapdoor;
  • the object that meets the preset conditions is determined as the query result; wherein, the index of any object is the first obtained according to the spatial position and keyword set of the object.
  • the second lower triangular matrix is obtained after being encrypted by the second encryption matrix.
  • processing module is specifically used for:
  • the keyword dictionary is obtained by taking the union of the keyword sets of each object in the space text data set;
  • the jth dimension element of the first vector is assigned a value of 0;
  • the first vector after the assignment of each dimension element is determined as the query key vector.
  • processing module is specifically used for:
  • the latitude value of the object is processed through n+1 latitude values of n+1 items and the longitude value of the object to determine the index space vector; the keyword set of the object is encoded to obtain index keyvector;
  • processing module is specifically used for:
  • processing module is specifically used for:
  • processing module is specifically used for:
  • the second lower triangular matrix obtained according to the spatial position of the object and the keyword set;
  • the index of the object is obtained by encrypting the second lower triangular square matrix according to the at least one random reversible square matrix, the third random lower triangular matrix and the fourth random lower triangular matrix.
  • the query curve includes a first query curve and a second query curve; each of the query sub-trapdoors includes a first query sub-trapdoor and a second query sub-trapdoor; the processing module is specifically used for:
  • an embodiment of the present invention also provides a computer device, including:
  • the processor is used to call the program instructions stored in the memory, and execute the above-mentioned spatial text query method according to the obtained program.
  • an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to cause a computer to execute the above spatial text query method.
  • FIG. 1 is a schematic diagram of a Gray code of spatial geographic coordinates provided by an embodiment of the present invention
  • FIG. 2 is a schematic diagram of a system architecture provided by an embodiment of the present invention.
  • FIG. 3 is a schematic flowchart of a spatial text query method provided by an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a query range provided by an embodiment of the present invention.
  • FIG. 5 is a schematic structural diagram of an application scenario provided by an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of a spatial text query device provided by an embodiment of the present invention.
  • the method for determining the query result based on the query range includes the following four stages:
  • the data owner generates a master key msk.
  • the spatial coordinates of Di are encoded as Gray codes. As shown in Figure 1, the object P is encoded as "0011"; then the keyword set of the object Di is encoded into a bitmap using the bitmap encoding method; finally, the Gray code based on the object and Bitmap generates object information vector;
  • the object information vector is encrypted according to the master key msk.
  • the query vector is encrypted according to the master key msk.
  • objects corresponding to the query keyword set within the query range are determined.
  • the preset coding algorithm can only determine the query range as a rectangle, as shown in Figure 1, it is impossible to determine the query range of a rectangle with each cell (such as "0011") as the basic unit. Query the query range of any shape, which cannot meet the actual needs of users.
  • the determined rectangular query range needs to include the city, but the rectangular query range includes the base of the city In addition, it will also include other regions, such as other cities, causing the banks within the rectangular query range to not only be limited to this city, but also include banks in other cities, resulting in the determined query results (banks) not targeting this city, resulting in
  • the determined query result includes objects not needed by the user, which reduces the accuracy of the query, and the determined query result has low precision.
  • the query request includes a query location and a query keyword. For example, if user A initiates a query request at a specific location, then this location is the query location of the query request, and the query location is generally a latitude and longitude coordinate value , the query point.
  • the query value is determined according to the preset weight, spatial distance and keyword similarity, and the query result is determined according to the size of the query value.
  • the spatial text corresponding to the maximum query value is used as the query result .
  • the index tree is constructed by the data owner based on the plaintext space text, and the smallest outer rectangle is the spatial range of the non-leaf nodes.
  • the problem with the above method is that the query value is related to the preset weight.
  • the query result is likely to appear different from that of the query.
  • the keywords in the request are similar nodes, so the determined query results include the ranking of the relevance value of the spatial text data leaked, and it is easy for the attacker to infer the information of each object according to the ranking of the relevance value, and may analyze the query
  • the user's daily habits and preferences have potential safety hazards.
  • FIG. 2 exemplarily shows a system architecture to which this embodiment of the present invention is applicable.
  • the system architecture includes a server 200 , and the server 200 may include a processor 210 , a communication interface 220 and a memory 230 .
  • the communication interface 220 is used for receiving query requests and sending query results.
  • the processor 210 is the control center of the server 200, and uses various interfaces and routes to connect various parts of the entire server 200, by running or executing software programs/or modules stored in the memory 230, and calling data stored in the memory 230, Various functions of the server 200 are performed and data is processed.
  • the processor 210 may include one or more processing units.
  • the memory 230 can be used to store software programs and modules, and the processor 210 executes various functional applications and data processing by running the software programs and modules stored in the memory 230 .
  • the memory 230 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application required by a function, etc.; the data storage area may store data created according to business processing, etc.
  • the memory 230 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.
  • FIG. 3 is only an example, which is not limited in this embodiment of the present invention.
  • FIG. 3 exemplarily shows a schematic flowchart of a spatial text query method provided by an embodiment of the present invention, and the process can be executed by a spatial text query device.
  • the process specifically includes:
  • Step 310 obtaining a query request.
  • the query request includes a query range and a query keyword set;
  • the query range is a closed area formed by a query curve; for example, the query range is an elliptical area formed by two curves, and the query keyword set Including query keywords as "Sichuan" and "hot pot”.
  • Step 320 encode the set of query keywords to obtain a query keyword vector.
  • the query keyword vector is obtained by determining whether the keyword recorded in the keyword dictionary exists in the query keyword set.
  • Step 330 for any query curve, perform polynomial fitting on the query curve, and determine coefficients of each power term of the fitted polynomial as a query range vector.
  • the query curve can be represented in a matrix to participate in the calculation.
  • Step 340 based on each query sub-trapdoor and the index of each object in the spatial text dataset, determine the object satisfying the preset condition as the query result.
  • the preset conditions include a first threshold and a second threshold, the first threshold is used to determine the object matching the query keyword set; the second threshold is used to determine the object matching the query range object.
  • the query range can be an area of any shape, and the query range can be a closed area formed by multiple query curves, and the number of query curves is not limited here;
  • FIG. 4 is an exemplary embodiment of the present invention.
  • the query keyword vector is obtained by establishing the first vector and assigning values to elements of each dimension in the first vector according to the keyword dictionary and the query keyword set.
  • a first vector is established; if it is determined that the jth keyword in the keyword dictionary is recorded in the query keyword set, the jth dimension of the first vector is The element is assigned a value of 1; if it is determined that the jth keyword in the keyword dictionary is not recorded in the query keyword set, then the jth dimension element of the first vector is assigned a value of 0; after assigning each dimension element The first vector is determined as the query key vector.
  • the keyword dictionary is obtained by taking the union of the keyword sets of each object in the spatial text data set; for example, given a spatial text data set D, the spatial text data set D includes the information of multiple objects (spatial position and keyword set), for example, the spatial text data set D includes multiple objects, taking the first object as an example; the spatial position coordinates of the first object are (x 1 , y 1 ), and the keyword set includes "Sichuan","spicy" and "hot pot". Among them, x 1 represents the latitude value of the first object, and y 1 represents the longitude value of the first object.
  • the first vector is ⁇ m1, m2, m3, m4 ⁇ ;
  • the first keyword in the dictionary W is "Sichuan”, and it is determined that the first keyword exists in the query keyword set, then the first dimension element (m1) in the first vector is assigned a value of 1; and so on, the second dimension element ( m2) is assigned a value of 0; the third dimension element (m3) is assigned a value of 0; the fourth dimension element (m4) is assigned a value of 1; thus the query key vector is determined to be ⁇ 1, 0, 0, 1 ⁇ .
  • the query range vector is determined according to the polynomial of the fitted curve, such as the fitted curve
  • the query range vector is ⁇ a 0 , a 1 ,..., a 10 ⁇ ; fitting curve
  • the query range vector of is ⁇ b 0 , b 1 ,..., b 10 ⁇ .
  • the constructed random lower triangular matrix is assigned based on the query range vector and the query key vector, so as to obtain the first lower triangular matrix representing the query range information of the fitting curve and the query key set.
  • the matrices are all square matrices.
  • the first random lower triangular matrix is determined based on the degree n of the highest power item in the polynomial and the number m of keywords in the keyword dictionary; according to the query range vector and the query keyword vector in each dimensional element pair The diagonals of the first random lower triangular matrix are assigned to obtain the first lower triangular matrix.
  • the lower triangular matrix is a matrix whose elements above the diagonal are all 0.
  • a (n+m+3) ⁇ (n+m+3)-dimensional lower triangular matrix E 1 (the first random lower triangular matrix) is randomly generated, Then assign values to the diagonals of the first random lower triangular matrix according to the elements of each dimension in the query range vector and the query key vector.
  • the coefficient of the rth power item in the query range vector is assigned to the element of the r+1th row and the r+1th column in the first random lower triangular matrix; 0 ⁇ r ⁇ n; -1 Assigning a value to the element of the n+2th row and the n+2th column in the first random lower triangular matrix; assigning the jth dimension element in the query key vector to the n+th element in the first random lower triangular matrix Elements in column n+2+j in row 2+j; assign the number of keywords in the query keyword set to the elements in the last row and last column in the first random lower triangular matrix.
  • the coefficient of the 0th power item in the query range vector is a 0
  • a 0 is assigned to the r+1th row and r+1th column in the first random lower triangular matrix E1
  • assign values corresponding to the elements of each dimension in the query range vector to the first random lower triangular matrix E1 ;
  • the quantity of keywords in the query keyword set (as the quantity of keywords in the above-mentioned query keyword set is 2) is assigned to the element of the last row and last column in the first random lower triangular matrix E1
  • the first fitting curve is obtained The first lower triangular matrix of Similarly, the second fitting curve The first lower triangular matrix of is
  • a second lower triangular matrix representing the spatial position of the object and a keyword set is stored; specifically, the second lower triangular matrix is obtained in the following manner, including: based on The degree n of the highest power item in the polynomial and the keyword quantity m in the keyword dictionary determine the second random lower triangular matrix; for any object, the latitude value of the object is n+1 processed by n+1 times The item latitude value and the longitude value of the object determine the index space vector; the key set of the object is encoded to obtain the index key vector; according to the index space vector and the elements of each dimension in the index key vector Assign values to the diagonals of the second random lower triangular matrix to obtain a second lower triangular matrix.
  • the keyword set of the i-th object o i includes the keywords "spicy” and "barbecue", then according to the above method for determining the query keyword vector, the index keyword vector of the object is determined to be ⁇ 0, 0, 0 ,0 ⁇ .
  • the spatial position of object o i is ( xi , y i ); wherein, the latitude value of object o i of x i , the longitude value of object o i of y i ; then determine the index space vector as After obtaining the index space vector and the index key vector of the object o i , assign a value to the diagonal E2 of the second random lower triangular matrix; specifically, assign the latitude value of the object's latitude value after r times of processing To the element of row r+1 and column r+1 in the second random lower triangular matrix; 0 ⁇ r ⁇ n; assign the longitude value of the object to the r+th row in the second random lower triangular matrix
  • the element in row r+2 in row 2; the element in dimension j in the index key vector is assigned to the element in row n+3+j in row n+3+j in the second random lower triangular matrix; Assign -1 to the elements in the last row and last column of the second
  • the first lower triangular matrix randomly generate a (n+m+3) ⁇ (n+m+3) dimension lower triangular matrix F 1 (the second random lower triangular matrix), Then assign values to the diagonals of the second random lower triangular matrix according to the index space vector and index key vector of the first object o1 .
  • the first lower triangular matrix and the second lower triangular matrix need to be encrypted.
  • the random reversible square moment, the third random lower triangular matrix, the third lower triangular matrix, the fourth random lower triangular matrix and the fourth lower triangular matrix are pre-generated and used as key components for information to encrypt.
  • the second lower triangular matrix of any object encrypt the second lower triangular square matrix according to the at least one random reversible square matrix, the third random lower triangular matrix and the fourth lower triangular matrix to obtain the index of the object; as index of object o i
  • step 340 for any object, by multiplying the index of the object by the first query sub-trapdoor R 1 and the second query sub-trapdoor R 2 respectively, it is determined whether the object satisfies a preset condition.
  • a first result matrix is determined based on the index of the object and the first query sub-trapdoor;
  • a second result matrix is determined based on the index of the object and the second query sub-trapdoor; determining the trace of the first result matrix and the trace of the second result matrix, and determining whether the object satisfies a preset condition according to the trace of the first result matrix and the trace of the second result matrix.
  • the trace of the matrix is the sum of the elements on the diagonal of the matrix.
  • the first result matrix is tr(C i R 1 );
  • the second result matrix is tr(C i R 2 );
  • the preset conditions include:
  • the absolute value of the trace of the first result matrix and the absolute value of the trace of the second result matrix are less than a first threshold; and the trace of the first result matrix is greater than a second threshold; the trace of the second result matrix is smaller than a second threshold; wherein, the first threshold is used to determine objects that meet the query keyword set; and the second threshold is used to determine objects that meet the query range.
  • the first threshold value is 0.1; because in the third lower triangular matrix D2 , the value of the n+3th row n+3 column to the n+m+3th row n+m+3 column value is 1 , and the elements from row n+3, column n+3 to row n+m+3, column n+m+3 of the first lower triangular matrix and the second lower triangular matrix are used to represent keywords;
  • the value of the first row and the first column to the n+2th row n+2 column is set to 0.001 (preset positive real number), and the first lower triangular matrix and the second lower triangular matrix
  • 0.001 preset positive real number
  • K the trace of the result matrix will be smaller because of the preset positive real number (0.001), therefore, if the absolute value of the trace of the first result matrix and the absolute value of the trace of the second result matrix are not less than the first threshold, it proves that K and ⁇ are not equal, and the keyword of the object does not correspond to the query keyword, that is, the object cannot be used as the query result; otherwise, the object has the prerequisite requirements for the query result.
  • the first result matrix is used to characterize the first query sub-trapdoor, and the first query sub-trapdoor corresponds to the first query curve ⁇ 1 (shown by the dotted line in Figure 4), and in the spatial position, the first The query curve ⁇ 1 is located in the upper half, therefore, if the trace of the first result matrix is greater than 0 (the second threshold), it indicates that the object is located below the first query curve ⁇ 1 ; if the trace of the second result matrix is less than 0 ( second threshold), it indicates that the object is located above the second query curve ⁇ 1 .
  • the object is determined as the query result.
  • FIG. 5 exemplarily shows a schematic structural diagram of an application scenario, as shown in FIG. 5 , including a data owner 510, a cloud server 520, and a client 530;
  • the data owner 510 determines at least one random reversible square matrix, the third lower triangular matrix, the fourth lower triangular matrix, the third random lower triangular matrix and the fourth random lower triangular matrix, and at least one random reversible square matrix, the third The lower triangular matrix, the fourth lower triangular matrix, the third random lower triangular matrix and the fourth random lower triangular matrix are used as key components; the data owner 510 uses at least one inverse matrix of the random reversible square matrix, the third lower triangular matrix, The fourth lower triangular matrix is sent to the client 530;
  • the data owner 510 determines the second lower triangular matrix for each object in the spatial text dataset, and calculates the second lower triangular matrix of each object based on at least one random reversible square matrix, the third random lower triangular matrix and the fourth random lower triangular matrix
  • the matrix is encrypted to obtain the index of each object; and the index is sent to the cloud server 520;
  • the client 530 determines the first lower triangular matrix of the first query curve and the second query curve based on the query range and the query keyword set of the query request, and according to the inverse matrix of at least one random reversible square matrix sent by the data owner 510 , the third lower triangular matrix, and the fourth lower triangular matrix encrypt the first lower triangular matrix, determine the query sub-trapdoors of the first query curve and the second query curve, and query the first query curve and the second query curve The sub-trapdoor is sent to the cloud server 520.
  • the cloud server 520 determines the object satisfying the preset condition as the query result, and returns the query result to the client 530 .
  • FIG. 6 exemplarily shows a schematic structural diagram of a spatial text query device provided by an embodiment of the present invention, and the device can execute a flow of a spatial text query method.
  • the device specifically includes:
  • An acquisition module 610 configured to acquire a query request; the query request includes a query range and a query keyword set; the query range is a closed area formed by a query curve;
  • a processing module 620 configured to encode the set of query keywords to obtain a query keyword vector
  • polynomial fitting is performed on the query curve, and the coefficients of each power term of the fitted polynomial are determined as a query range vector; based on the query range vector and the query keyword vector, get The first lower triangular matrix; encrypting the first lower triangular matrix through the first encryption matrix to obtain the query sub-trapdoor;
  • the object that meets the preset conditions is determined as the query result; wherein, the index of any object is the first obtained according to the spatial position and keyword set of the object.
  • the second lower triangular matrix is obtained after being encrypted by the second encryption matrix.
  • processing module 620 is specifically configured to:
  • the keyword dictionary is obtained by taking the union of the keyword sets of each object in the space text data set;
  • the jth dimension element of the first vector is assigned a value of 0;
  • the first vector after the assignment of each dimension element is determined as the query key vector.
  • processing module 620 is specifically configured to:
  • the latitude value of the object is processed through n+1 latitude values of n+1 items and the longitude value of the object to determine the index space vector; the keyword set of the object is encoded to obtain index keyvector;
  • processing module 620 is specifically configured to:
  • processing module 620 is specifically configured to:
  • processing module 620 is specifically configured to:
  • the second lower triangular matrix obtained according to the spatial position of the object and the keyword set;
  • the index of the object is obtained by encrypting the second lower triangular square matrix according to the at least one random reversible square matrix, the third random lower triangular matrix and the fourth random lower triangular matrix.
  • the query curve includes a first query curve and a second query curve; each of the query sub-trapdoors includes a first query sub-trapdoor and a second query sub-trapdoor; the processing module 620 is specifically configured to:
  • the embodiment of the present invention also provides a computer device, including:
  • the processor is used to call the program instructions stored in the memory, and execute the above-mentioned spatial text query method according to the obtained program.
  • the embodiment of the present invention also provides a computer-readable storage medium, the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to make the computer execute the above-mentioned spatial text query method.
  • the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions
  • the device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

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Abstract

Un procédé et un appareil d'interrogation de texte spatial sont divulgués dans la présente invention. Le procédé consiste : à obtenir une demande d'interrogation, la demande d'interrogation comprenant une plage d'interrogation et un ensemble de mots-clés d'interrogation, et la plage d'interrogation étant une région fermée formée par une courbe d'interrogation ; à coder l'ensemble de mots-clés d'interrogation pour obtenir un vecteur de mot-clé d'interrogation ; à effectuer un ajustement polynomial sur la courbe d'interrogation pour déterminer un vecteur de plage d'interrogation ; à obtenir une première matrice triangulaire inférieure sur la base du vecteur de plage d'interrogation et du vecteur de mot-clé d'interrogation ; à chiffrer la première matrice triangulaire inférieure au moyen d'une première matrice de chiffrement afin d'obtenir une porte de sous-piège d'interrogation ; et sur la base de chaque porte de sous-piège d'interrogation et de l'indice de chaque objet dans un ensemble de données de texte spatial, à déterminer un objet satisfaisant des conditions préétablies comme étant un résultat d'interrogation, l'indice de n'importe quel objet étant obtenu par chiffrement, au moyen d'une seconde matrice de chiffrement, une seconde matrice triangulaire inférieure qui est obtenue en fonction de la position spatiale de l'objet et d'un ensemble de mots-clés. Par conséquent, la présente invention satisfait la plage d'interrogation réellement requise par un utilisateur, et améliore la précision d'interrogation.
PCT/CN2021/135363 2021-10-18 2021-12-03 Procédé et appareil d'interrogation de texte spatial WO2023065477A1 (fr)

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